The correct differentiation and use of synonyms and quasi-synonyms in both oral and written communication is not only something that is found to be difficult by students studying a language as a foreign language, but is unexpectedly so even for native speakers using the language in their daily lives. Word processing software, foreign language instructional software, translation software and the like have come to be widely used in recent years. Software programs such as these have various support functions for performing input, editing, and output; however, none have implemented functionality for automatically providing the user with recommendations and differentiations based on differences in usage examples of a target word so as to enable the user to use the target word accurately.
One attempt at determining which types of words a target word can be easily used with is research in the field of linguistics studying the frequency of co-occurrence of words (Non-patent reference No. 1). In the aforementioned research, the structure of an inputted sentence is analyzed, the words appearing in the sentence that are found to share a structural relationship are subjected to a process for eliminating any randomness in the emerging association and for measuring a co-occurrence score; the scores are sorted, and words having a high score are deemed to share a deep structural relationship. In this case, if the synonyms having a high score among a plurality of synonyms that are target words are extracted, it becomes possible to estimate which types of usage examples there are for each respective synonym.    Non-patent Reference No. 1: Stefan Th. Gries and Anatol Stefanowitsch, “Extending collostructional analysis: A corpus-based perspective on alternations”, International Journal of Corpus Linguistics, 9:1, 2004